Abstract
Model Based Transformation Example (MTBE) is a recent track of research aiming at learning a transformation from examples. In most MTBE processes, a transformation example is given in the form of a source model, a transformed model and links between source elements and the corresponding transformed elements. Building the links is done manually, which is a tedious task, while in many cases, they can be deduced from the examination of the source and transformed models, by using relevant attributes, like names or identifiers. We exploit this characteristic by proposing a semi-automatic matching operation, suitable for discovering matches between the source model and the transformed model. Our technique is inspired by and extends the Anchor-Prompt approach, and is based on the automatic discovery of pairs of anchors (pairs of elements for which there is a strong assumption of matching) to support the whole matching discovery. An implementation of the approach is provided for validation on a case study.
This research was partially supported by the european project OPEES.
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References
OMG: MOF QVT Final Adopted Specification. Object Modeling Group (2005)
Lopes, D., Hammoudi, S., Bézivin, J., Jouault, F.: Generating transformation definition from mapping specification: Application to web service platform. In: Pastor, Ó., Falcão e Cunha, J. (eds.) CAiSE 2005. LNCS, vol. 3520, pp. 309–325. Springer, Heidelberg (2005)
Falleri, J.R., Huchard, M., Lafourcade, M., Nebut, C.: Metamodel matching for automatic model transformation generation. In: Busch, C., Ober, I., Bruel, J.-M., Uhl, A., Völter, M. (eds.) MODELS 2008. LNCS, vol. 5301, pp. 326–340. Springer, Heidelberg (2008)
Wimmer, M., Strommer, M., Kargl, H., Kramler, G.: Towards model transformation generation by-example. In: HICSS 2007: Proc. of the 40th Annual Hawaii International Conf. on System Sciences, p. 285b. IEEE Computer Society, Los Alamitos (2007)
Balogh, Z., Varró, D.: Model transformation by example using inductive logic programming. Software and Systems Modeling (2008) (appeared online)
Dolques, X., Huchard, M., Nebut, C.: From transformation traces to transformation rules: Assisting model driven engineering approach with formal concept analysis. In: Proceedings of ICCS 2009 Supplementary, pp. 15–29 (2009)
Kessentini, M., Sahraoui, H., Boukadoum, M.: Model Transformation as an Optimization Problem. In: Busch, C., Ober, I., Bruel, J.-M., Uhl, A., Völter, M. (eds.) MODELS 2008. LNCS, vol. 5301, pp. 159–173. Springer, Heidelberg (2008)
Rahm, E., Bernstein, P.A.: A survey of approaches to automatic schema matching. VLDB J. 10(4), 334–350 (2001)
Shvaiko, P., Euzenat, J.: A survey of schema-based matching approaches. In: Spaccapietra, S. (ed.) Journal on Data Semantics IV. LNCS, vol. 3730, pp. 146–171. Springer, Heidelberg (2005)
Noy, N.F., Musen, M.A.: Anchor-prompt: Using non-local context for semantic matching. In: Proc. of the Workshop on Ontologies and Information Sharing at IJCAI 2001, Seattle, USA, pp. 63–70 (2001)
Dolques, X., Huchard, M., Nebut, C., Reitz, P.: Learning transformation rules from transformation examples: An approach based on relational concept analysis. In: 14th IEEE International Enterprise Distributed Object Computing Conference Workshops of EDOC 2010, pp. 27–32. IEEE Computer Society Press, Los Alamitos (2010)
Do, H.H., Melnik, S., Rahm, E.: Comparison of schema matching evaluations. In: Chaudhri, A.B., Jeckle, M., Rahm, E., Unland, R. (eds.) NODe-WS 2002. LNCS, vol. 2593, pp. 221–237. Springer, Heidelberg (2003)
Fowler, M., Beck, K., Brant, J., Opdyke, W., Roberts, D.: Refactoring: Improving the Design of Existing Code. Addison-Wesley, Reading (2000)
ATL transformation zoo, http://www.eclipse.org/m2m/atl/atlTransformations/
Melnik, S., Garcia-Molina, H., Rahm, E.: Similarity flooding: A versatile graph matching algorithm and its application to schema matching. In: ICDE, pp. 117–128. IEEE Computer Society, Los Alamitos (2002)
Do, H.H., Rahm, E.: Coma - a system for flexible combination of schema matching approaches. In: VLDB, pp. 610–621. Morgan Kaufmann, San Francisco (2002)
Madhavan, J., Bernstein, P.A., Rahm, E.: Generic schema matching with cupid. In: VLDB, pp. 49–58. Morgan Kaufmann, San Francisco (2001)
Ehrig, M., Staab, S.: QOM – quick ontology mapping. In: McIlraith, S.A., Plexousakis, D., van Harmelen, F. (eds.) ISWC 2004. LNCS, vol. 3298, pp. 683–697. Springer, Heidelberg (2004)
Euzenat, J., Loup, D., Touzani, M., Valtchev, P.: Ontology Alignment with OLA. In: Proc. of the 3rd EON Workshop, 3rd Int. Semantic Web Conf, pp. 333–337 (2004)
Fabro, M.D.D., Valduriez, P.: Towards the efficient development of model transformations using model weaving and matching transformations. Software and System Modeling 8(3), 305–324 (2009)
Wimmer, M., Strommer, M., Kargl, H., Kramler, G.: Towards model transformation generation by-example. In: HICSS, p. 285. IEEE Computer Society, Los Alamitos (2007)
Langer, P., Wimmer, M., Kappel, G.: Model-to-model transformations by demonstration. In: Tratt, L., Gogolla, M. (eds.) ICMT 2010. LNCS, vol. 6142, pp. 153–167. Springer, Heidelberg (2010)
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Dolques, X., Dogui, A., Falleri, JR., Huchard, M., Nebut, C., Pfister, F. (2011). Easing Model Transformation Learning with Automatically Aligned Examples. In: France, R.B., Kuester, J.M., Bordbar, B., Paige, R.F. (eds) Modelling Foundations and Applications. ECMFA 2011. Lecture Notes in Computer Science, vol 6698. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-21470-7_14
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DOI: https://doi.org/10.1007/978-3-642-21470-7_14
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